The present disclosure relates generally to methods for automated seismic data interpretation in seismic volumes of data, and more particularly, relates to automated seismic interpretation to run horizon auto-picking on a based volume and to then associate the auto-picked horizon with a plurality of seismic volumes.
Seismic reflection surveys, both land and marine, are often performed using seismic data acquisition methods to collect seismic data. This provides a volume of the earth's stratigraphy for identifying geological structures, such as horizons and faults in the Earth's subsurface. Seismic reflection is a method of generating seismic waves and measuring the time taken for the seismic waves to travel from the source of the waves, reflect off an interface, and be detected by an array of receivers at the surface. Each receiver's response to a single shot of seismic energy is known as a trace and is recorded for analysis. In land acquisition, seismic waves are transmitted from the surface, produced either mechanically or by explosive device. Resulting reflections from the subsurface are received at geophone sensors. In marine data acquisition surveying geological structures underlying a body of water, a water-going vessel is utilized to tow acoustic sources and seismic streamers supporting an array of hydrophones to detect reflected seismic waves.
Interpretation of seismic reflection surveys often involves analyzing multiple volumes of data containing structural information (e.g., faults or horizons) and seismic information (e.g., seismic amplitude). Interrelationships between these multiple volumes of data are becoming increasingly important for exploration, development, and production purposes. Furthermore, there has been an increase in the number of surveys performed and data types recorded, increasing the number of seismic volumes of data that must be interpreted. Manual interpretation across multiple volumes of data, such as an interpreter manually picking horizon data in one volume and re-interpreting the horizon data on other volumes, is very time-consuming. An additional inconvenience occurs when a change to an initial interpretation of manually picked horizon data causes a need to manually update horizon interpretations on the other seismic volumes. A method for automatically updating the other volumes with any changes in interpretation would aid in management of the large number of seismic volumes that interpreters are faced with and increase precision of interpretations by reducing inaccuracies resulting from tedious manual interpretation of horizon data.